The management of uncertainty and imprecision is becoming more and more important in knowledge-based systems. Fuzzy logic provides a systematic basis for representing and inferring with this kind of knowledge. This paper describes an approach for fuzzy inference based on an uncertainty forward propagation method and a change in the granularity of the elements involved. The proposed model is abl...

The fuzzy systems and control are regarded as the most widely used application of fuzzy logic systems in recent years (Jang, 1993; John & Coupland, 2007; Lin & Lee, 1006; Mendel, 2001; Wang, 1994). The structure of traditional fuzzy system models that is characterized by using type 1 fuzzy sets, which are defined on a universe of discourse, map an element of the universe of discourse onto a pre...

Random early detection (RED) is the most popular active queue management algorithm that is used by the Internet routers. This paper proposes a neuro-fuzzy controller which enhances the network performance by dynamically tuning of RED's maxp parameter. The controller first learns the network behavior against maxp variations and then adjusts maxp. Simulation results in ns-2 environment show that,...

In this paper we have introduced a non interactive model for fuzzy rule based systems A critical aspects of this non interactive model is the introduction of a new set of rules with fewer parameters and without considering the interaction between the functionality of inputs The new non interactive model of the fuzzy rule based system represents the output as a linear combination of the non line...

" In this paper, we define a fuzzy imperative programming language (called L), powerful enough to express crisp and fuzzy algorithms. Its small instruction set is designed to enhance readability, and it is proved before that the class of functions that can be programmed in L is equivalent to the class of functions computed by a W-Turing machine and to the W-recursive functions. The language is ...

Fuzzy ARTMAP (FAM) is currently considered as one of the premier neural network architectures in solving classification problems. One of the limitations of Fuzzy ARTMAP that has been extensively reported in the literature is the category proliferation problem. That is, Fuzzy ARTMAP has the tendency of increasing its network size as it is confronted with more and more data, especially if the dat...

We consider the problem of building robust fuzzy extractors, which allow two parties holding similar random variables W , W ′ to agree on a secret key R in the presence of an active adversary. Robust fuzzy extractors were defined by Dodis et al. in Crypto 2006 [6] to be noninteractive, i.e., only one message P , which can be modified by an unbounded adversary, can pass from one party to the oth...

We consider the problem of building robust fuzzy extractors, which allow two parties holding similar random variables W , W ′ to agree on a secret key R in the presence of an active adversary. Robust fuzzy extractors were defined by Dodis et al. in Crypto 2006 [6] to be noninteractive, i.e., only one message P , which can be modified by an unbounded adversary, can pass from one party to the oth...

The Simpliied Adaptive Resonance Theory (SART) class of networks is proposed to handle problems encountered in Adaptive Resonance Theory 1 (ART 1)-based algorithms when detection of binary and analog patterns is performed. The basic idea of SART is to substitute ART 1-based \unidirectional" (asymmetric) activation and match functions with \bidirectional" (symmetric) function pairs. This substit...

The concept of upper and lower semicontinuity of fuzzy mappings introduced by Bao and Wu [Y.E. Bao, C.X. Wu, Convexity and semicontinuity of fuzzy mappings, Comput. Math. Appl., 51 (2006) 1809–1816] is redefined by using the concept of parameterized triples of fuzzy numbers. On the basis of the linear ordering of fuzzy numbers proposed by Goetschel and Voxman [R. Goetschel, W. Voxman, Elementar...